Advancements in Legged Robot Locomotion and Manipulation

The field of legged robotics is rapidly advancing, with a focus on developing more agile, adaptable, and robust systems. Recent research has emphasized the importance of whole-body control, dynamic obstacle avoidance, and multimodal sensing for quadrupedal and bipedal robots. Notably, the integration of reinforcement learning, model predictive control, and spiking neural networks has enabled significant improvements in locomotion and manipulation capabilities.

One of the key directions in this field is the development of control frameworks that can seamlessly integrate high-level task planning with low-level whole-body control. This has led to the creation of more autonomous and adaptable robots that can navigate complex environments and perform a variety of tasks.

Another area of focus is the development of more efficient and robust methods for learning agile locomotion behaviors. This includes the use of unsupervised skill discovery, curriculum learning, and bi-level optimization to enable robots to acquire a diverse repertoire of skills for overcoming obstacles.

Some noteworthy papers in this area include: REBot, which introduces a control framework for quadrupedal robots to achieve real-time reflexive obstacle avoidance. ODYSSEY, which presents a unified mobile manipulation framework for agile quadruped robots equipped with manipulators, seamlessly integrating high-level task planning with low-level whole-body control. Whole-Body Coordination for Dynamic Object Grasping with Legged Manipulators, which introduces DQ-Bench, a new benchmark for evaluating dynamic grasping, and DQ-Net, a compact teacher-student framework for inferring grasp configurations from limited perceptual cues.

Sources

REBot: Reflexive Evasion Robot for Instantaneous Dynamic Obstacle Avoidance

Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robots

Learning a Vision-Based Footstep Planner for Hierarchical Walking Control

Multimodal Spiking Neural Network for Space Robotic Manipulation

LAURON VI: A Six-Legged Robot for Dynamic Walking

ODYSSEY: Open-World Quadrupeds Exploration and Manipulation for Long-Horizon Tasks

Koopman Operator Based Linear Model Predictive Control for Quadruped Trotting

Whole-Body Coordination for Dynamic Object Grasping with Legged Manipulators

Unsupervised Skill Discovery as Exploration for Learning Agile Locomotion

Large Scale Robotic Material Handling: Learning, Planning, and Control

CLF-RL: Control Lyapunov Function Guided Reinforcement Learning

PPL: Point Cloud Supervised Proprioceptive Locomotion Reinforcement Learning for Legged Robots in Crawl Spaces

Hybrid Data-Driven Predictive Control for Robust and Reactive Exoskeleton Locomotion Synthesis

MLM: Learning Multi-task Loco-Manipulation Whole-Body Control for Quadruped Robot with Arm

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